Publication date: Jul 28, 2025

Real-world data reported by patients and extracted from electronic health records (EHRs) are increasingly leveraged for research, policy, and clinical decision-making. However, it is not always obvious the extent to which these 2 data sources agree with each other. This study aimed to evaluate the concordance of variables reported by participants enrolled in an electronic cohort study and data available in their EHRs. Survey data from COVID-19 Citizen Science, an electronic cohort study, were linked to EHR data from 7 health systems, comprising 34,908 participants. Concordance was evaluated for demographics, chronic conditions, and COVID-19 characteristics. Overall agreement, sensitivity, specificity, positive predictive value, negative predictive value, and _705 statistics with 95% CIs were calculated. Of 34,017 participants with complete information, 62. 3% (21,176/34,017) reported being female, and 62. 4% (21,217/34,017) were female according to EHR data. The median age was 57 (IQR 42-68) years. Out of 34,017 participants, 81. 6% (27,744/34,017) of participants reported being White, and 79. 5% (27,054/34,017) were White according to EHR data. In addition, 9. 2% (3,124/34,017) of participants reported being Hispanic, and 6. 6% (2,249/34,017) were Hispanic according to EHR data. Statistically significant discordance between data sources was detected for all demographic characteristics (P

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